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Fluctuation Induced Network Control and Learning

From theory to application, this book presents research on biologically and brain-inspired networking and machine learning based on Yuragi;

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Tracking Control of Networked Systems via Sliding-Mode

induced delay, out-of-sequence and packet loss, and network attacks are studied in detail. The content studied in this book is introduced;

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Nonlinear Stochastic Systems with Network-Induced Phenomena

This monograph introduces methods for handling filtering and control problems in nonlinear stochastic systems arising from network-induced;

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Networked and Event-Triggered Control Approaches in Cyber-Physical Systems

network-induced uncertainties may degrade system control performance. Thus, this book researches networked delay compensation and event-triggered;

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Robot Control using an Artificial Neural Network

artificial neural network type were considered. An introduction to learning and control structures using artificial neural networks were given. These;

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Nonlinear Control and Filtering for Stochastic Networked Systems

concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities;

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Nonlinear Control and Filtering for Stochastic Networked Systems

concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities;

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Battery Energy Storage Systems for Photovoltaic Sources

The generation intermittency resultant from a large photovoltaic (PV) system connected to the power network introduces many challenges and;

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Neural Fuzzy Control Systems With Structure And Parameter Learning

fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a;

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Neural Networks for Control

Neural Networks for Control highlights key issues in learning control and identifies research directions that could lead to practical;

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Artificial Neural Networks

-layered learning network based on simple math rules. The structure of an artificial neural network consists of an input layer, an output layer and;

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Fluctuation Mechanism and Control on System Instantaneous Availability

Fluctuation Mechanism and Control on System Instantaneous Availability facilitates the development of modeling and identification skills;

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Call Admission Control in a Mobile Cellular Network

of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load;

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Networked Predictive Control of Systems with Communication Constraints and Cyber Attacks

This book presents the latest results on predictive control of networked systems, where communication constraints (e.g., network-induced;

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Implementing Cisco IOS Network Security (IINS 640-554) Foundation Learning Guide

the use of Cisco Catalyst switches for basic network security, the Cisco Secure Access Control System (ACS), and the Cisco Adaptive Security;

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Network Models for Control and Processing

: control solutions using theoretical computational learning models, learning algorithms and polynomial networks; simulating biological;

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Proceedings of 2017 Chinese Intelligent Automation Conference

control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for;

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Advances in Computing Communication and Control

This book constitutes the refereed proceedings of the International Conference on Advances in Computing Communications and Control, ICAC3;

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Intelligent Control Based on Flexible Neural Networks

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 4. 3 Flexible Neural Network as an Indirect Controller . . . . . . . . . . . . . . . 91 4. 4 Self-tunig PID Control;

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Neural Network Control of Nonlinear Discrete-Time Systems

neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control;

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Proceedings of 2013 Chinese Intelligent Automation Conference

control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control;

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Proceedings of 2013 Chinese Intelligent Automation Conference

control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control;

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Proceedings of 2013 Chinese Intelligent Automation Conference

control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control;

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Optimal Networked Control Systems with MATLAB

communication network Covers distributed joint optimal network scheduling and control design for wireless NCS, as well as the effect of network;

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Optimal Networked Control Systems With MATLAB

distributed NCS to minimize transmission of state and control signals within the feedback loop via the communication network Covers distributed joint;

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Computing Algorithms with Applications in Engineering

virtualization, cognitive systems, swarm intelligence, human-computer interaction, network and information security, intelligent control, soft computing;

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